Implementation of a Federated Large-Scale Remote Sensing Data Sharing Platform

Xuan Ma; Zhibao Wang; Lu Bai; Bingbing Xu; Juntao Gao; Bilong Wen; Jinhua Tao

doi:10.1109/IGARSS47720.2021.9554247

Implementation of a Federated Large-Scale Remote Sensing Data Sharing Platform

Xuan Ma, Zhibao Wang, Lu Bai, Bingbing Xu, Juntao Gao, Bilong Wen, Jinhua Tao

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

In this paper, a unified virtual cloud storage method for federated data based on the middle layer is proposed, which aims at solving the problems of the heterogeneous data sources of remote sensing data in the shared platform among the federated remote sensing data management application under loose coupling mode. A federated remote sensing image data management model is developed based on NASA's Unified Metadata Model (UMM). This platform implements services such as unified access to multi-source heterogeneous image data which effectively solves the problem of heterogeneous data sources in the loosely coupled federated system, and provides better access methods for upper-level applications.

Original language	English
Title of host publication	2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS
Publisher	IEEE
Pages	5771-5774
Number of pages	4
ISBN (Electronic)	978-1-6654-0369-6, 978-1-6654-0368-9
ISBN (Print)	978-1-6654-4762-1
DOIs	https://doi.org/10.1109/IGARSS47720.2021.9554247
Publication status	Published (in print/issue) - 12 Oct 2021
Event	IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium - Brussels, Belgium Duration: 11 Jul 2021 → 16 Jul 2021

Conference

Conference	IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium
Period	11/07/21 → 16/07/21

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/IGARSS47720.2021.9554247

Cite this

@inproceedings{557a0a5b9cea4fa4a48429ef8d56e2f3,

title = "Implementation of a Federated Large-Scale Remote Sensing Data Sharing Platform",

abstract = "In this paper, a unified virtual cloud storage method for federated data based on the middle layer is proposed, which aims at solving the problems of the heterogeneous data sources of remote sensing data in the shared platform among the federated remote sensing data management application under loose coupling mode. A federated remote sensing image data management model is developed based on NASA's Unified Metadata Model (UMM). This platform implements services such as unified access to multi-source heterogeneous image data which effectively solves the problem of heterogeneous data sources in the loosely coupled federated system, and provides better access methods for upper-level applications.",

author = "Xuan Ma and Zhibao Wang and Lu Bai and Bingbing Xu and Juntao Gao and Bilong Wen and Jinhua Tao",

year = "2021",

month = oct,

day = "12",

doi = "10.1109/IGARSS47720.2021.9554247",

language = "English",

isbn = "978-1-6654-4762-1",

pages = "5771--5774",

booktitle = "2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS",

publisher = "IEEE",

address = "United States",

note = "IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium ; Conference date: 11-07-2021 Through 16-07-2021",

}

Ma, X, Wang, Z, Bai, L, Xu, B, Gao, J, Wen, B & Tao, J 2021, Implementation of a Federated Large-Scale Remote Sensing Data Sharing Platform. in 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS. IEEE, pp. 5771-5774, IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, 11/07/21. https://doi.org/10.1109/IGARSS47720.2021.9554247

TY - GEN

T1 - Implementation of a Federated Large-Scale Remote Sensing Data Sharing Platform

AU - Ma, Xuan

AU - Wang, Zhibao

AU - Bai, Lu

AU - Xu, Bingbing

AU - Gao, Juntao

AU - Wen, Bilong

AU - Tao, Jinhua

PY - 2021/10/12

Y1 - 2021/10/12

N2 - In this paper, a unified virtual cloud storage method for federated data based on the middle layer is proposed, which aims at solving the problems of the heterogeneous data sources of remote sensing data in the shared platform among the federated remote sensing data management application under loose coupling mode. A federated remote sensing image data management model is developed based on NASA's Unified Metadata Model (UMM). This platform implements services such as unified access to multi-source heterogeneous image data which effectively solves the problem of heterogeneous data sources in the loosely coupled federated system, and provides better access methods for upper-level applications.

AB - In this paper, a unified virtual cloud storage method for federated data based on the middle layer is proposed, which aims at solving the problems of the heterogeneous data sources of remote sensing data in the shared platform among the federated remote sensing data management application under loose coupling mode. A federated remote sensing image data management model is developed based on NASA's Unified Metadata Model (UMM). This platform implements services such as unified access to multi-source heterogeneous image data which effectively solves the problem of heterogeneous data sources in the loosely coupled federated system, and provides better access methods for upper-level applications.

UR - https://ieeexplore.ieee.org/document/9554247/

U2 - 10.1109/IGARSS47720.2021.9554247

DO - 10.1109/IGARSS47720.2021.9554247

M3 - Conference contribution

SN - 978-1-6654-4762-1

SP - 5771

EP - 5774

BT - 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS

PB - IEEE

T2 - IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium

Y2 - 11 July 2021 through 16 July 2021

ER -

Implementation of a Federated Large-Scale Remote Sensing Data Sharing Platform

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